• Prof. Dr. Snehal Bhosale
• Prerna Gajanan Honwalkar

With the continuous evolution of the Internet, as well as the development of the Internet of Things, smart terminals, cloud platforms, and social platforms, botnets are showing the characteristics of platform diversification, communication concealment, and control intelligence. A botnet is a group of computers linked to the Internet which have been compromised and are being controlled remotely by the botmaster through malicious software called bots. This survey analyzes and compares the most important efforts in the botnet detection area in recent years. It studies the mechanism characteristics of botnet architecture, and command and control channel (C&C) and provides a classification of botnet detection techniques. It focuses on the application of advanced technologies such as deep learning, complex network, and software-defined network (SDN) for botnet detection. While, many challenges remain unaddressed, such as the ability to design detectors that can cope with new forms of botnets. So there is a need for an advanced system that can detect traffic behavior accurately.

Security, Botnet Activity Detection, Machine learning, C&C, Feed Forward Neural Network.

"Botnet Detection Techniques using Machine Learning: Review", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 3, page no.b527-b533, March-2022, Available :http://www.jetir.org/papers/JETIR2203169.pdf

"Botnet Detection Techniques using Machine Learning: Review", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 3, page no. ppb527-b533, March-2022, Available at : http://www.jetir.org/papers/JETIR2203169.pdf